Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
Q8WYN0

UPID:
ATG4A_HUMAN

ALTERNATIVE NAMES:
AUT-like 2 cysteine endopeptidase; Autophagy-related cysteine endopeptidase 2; Autophagy-related protein 4 homolog A

ALTERNATIVE UPACC:
Q8WYN0; A6NCH2; B2RAZ7; D3DUY0; O95534; Q5JYY9; Q5JYZ0; Q86VE5; Q96KQ0; Q96KQ1

BACKGROUND:
The Cysteine protease ATG4A, known for its roles in autophagy, specifically targets ATG8 family proteins for proteolytic activation and delipidation. It reveals a C-terminal glycine essential for ATG8 protein conjugation, facilitating their role in autophagy. ATG4A's activity is crucial for maintaining autophagic flux by preventing ATG8ylation and ensuring the proper turnover of autophagic components. Its preference for GABARAPL2, MAP1LC3A, and GABARAP as substrates underlines its selective protease function.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Cysteine protease ATG4A could open doors to potential therapeutic strategies.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.